[HTML][HTML] Evolving cybersecurity frontiers: A comprehensive survey on concept drift and feature dynamics aware machine and deep learning in intrusion detection …
Abstract Intrusion Detection Systems (IDS) have become pivotal in safeguarding information
systems against evolving threats. Concurrently, Concept Drift presents a significant …
systems against evolving threats. Concurrently, Concept Drift presents a significant …
Integration of deep learning into the iot: A survey of techniques and challenges for real-world applications
The internet of things (IoT) has emerged as a pivotal technological paradigm facilitating
interconnected and intelligent devices across multifarious domains. The proliferation of IoT …
interconnected and intelligent devices across multifarious domains. The proliferation of IoT …
Leveraging machine learning for cybersecurity resilience in industry 4.0: Challenges and future directions
J Yu, AV Shvetsov, SH Alsamhi - IEEE Access, 2024 - ieeexplore.ieee.org
Industry 4.0, where the convergence of digital technology impacts industrial operations and
processes, is characterized by cybersecurity resilience. Therefore, in Industry 4.0, Machine …
processes, is characterized by cybersecurity resilience. Therefore, in Industry 4.0, Machine …
[HTML][HTML] Review on Hardware Devices and Software Techniques Enabling Neural Network Inference Onboard Satellites
Neural networks (NNs) have proven their ability to deal with many computer vision tasks,
including image-based remote sensing such as the identification and segmentation of …
including image-based remote sensing such as the identification and segmentation of …
Real‐time monitoring and ageing detection algorithm design with application on SiC‐based automotive power drive system
The article describes an innovative methodology for the design and experimental validation
of monitoring and anomaly detection algorithms, with a particular focus on the aging …
of monitoring and anomaly detection algorithms, with a particular focus on the aging …
Unveiling machine learning strategies and considerations in intrusion detection systems: a comprehensive survey
The advancement of communication and internet technology has brought risks to network
security. Thus, Intrusion Detection Systems (IDS) was developed to combat malicious …
security. Thus, Intrusion Detection Systems (IDS) was developed to combat malicious …
Design and Experimental Assessment of Real-Time Anomaly Detection Techniques for Automotive Cybersecurity
In recent decades, an exponential surge in technological advancements has significantly
transformed various aspects of daily life. The proliferation of indispensable objects such as …
transformed various aspects of daily life. The proliferation of indispensable objects such as …
ROAST-IoT: a novel range-optimized attention convolutional scattered technique for intrusion detection in IoT networks
A Mahalingam, G Perumal, G Subburayalu, M Albathan… - Sensors, 2023 - mdpi.com
The Internet of Things (IoT) has significantly benefited several businesses, but because of
the volume and complexity of IoT systems, there are also new security issues. Intrusion …
the volume and complexity of IoT systems, there are also new security issues. Intrusion …
[HTML][HTML] An efficient CNN-based intrusion detection system for IoT: Use case towards cybersecurity
Today's environment demands that cybersecurity be given top priority because of the
increase in cyberattacks and the development of quantum computing capabilities …
increase in cyberattacks and the development of quantum computing capabilities …